Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 359

The DOI matches its Crossref record.

Comparison of trends and low‐frequency variability in CRU, ERA‐40, and NCEP/NCAR analyses of surface air temperature

Open access
Simmons, A. J., Jones, P. D., da Costa Bechtold, V., Beljaars, A. C. M., Kållberg, P. W., Saarinen, S., Uppala, S. M., Viterbo, P., Wedi, N.·2004·Journal of Geophysical Research: Atmospheres

Abstract

Anomalies in monthly mean surface air temperature from the 45‐Year European Centre for Medium‐Range Weather Forecasts (ECMWF) Re‐Analysis (ERA‐40) and the first National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis are compared with corresponding values from the Climatic Research Unit (CRU) CRUTEM2v data set derived directly from monthly station data. There is mostly very similar short‐term variability, especially between ERA‐40 and CRUTEM2v. Linear trends are significantly lower for the two reanalyses when computed over the full period studied, 1958–2001, but ERA‐40 trends are within 10% of CRUTEM2v values for the Northern Hemisphere when computed from 1979 onward. Gaps in the availability of synoptic surface data contribute to relatively poor performance of ERA‐40 prior to 1967. A few highly suspect values in each of the data sets have also been identified. ERA‐40's use of screen‐level observations contributes to the agreement between the ERA‐40 and CRUTEM2v analyses, but the quality of the overall observing system and general character of the ERA‐40 data assimilation system are also contributing factors. Temperatures from ERA‐40 vary coherently throughout the boundary layer from the late 1970s onward, in general, and earlier for some regions. There is a cold bias in early years at 500 hPa over the data‐sparse southern extratropics and at the surface over Antarctica. One indicator of this comes from comparing the ERA‐40 analyses with results from a simulation of the atmosphere for the ERA‐40 period produced using the same model and same distributions of sea surface temperature and sea ice as used in the ERA‐40 data assimilation. The simulation itself reproduces quite well the warming trend over land seen in CRUTEM2v and captures some of the low‐frequency variability.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1029/2004jd005306

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 359

Metadata

Authors
Simmons, A. J., Jones, P. D., da Costa Bechtold, V., Beljaars, A. C. M., Kållberg, P. W., Saarinen, S., Uppala, S. M., Viterbo, P., & Wedi, N.
Venue
Journal of Geophysical Research: Atmospheres
Published
2004-12-27
Volume
109
Issue
D24
ISSN
0148-0227 (ISSN-L)
OpenAlex
W2059735239
Cited by
359
References
0
FWCI
21.24
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Comparison of trends and low‐frequency variability in CRU, ERA‐40, and NCEP/NCAR analyses of surface air temperature. https://app.cochat.ai/papers/10.1029/2004jd005306
The paper
Simmons, A. J., Jones, P. D., da Costa Bechtold, V., Beljaars, A. C. M., Kållberg, P. W., Saarinen, S., Uppala, S. M., Viterbo, P., & Wedi, N. (2004). Comparison of trends and low‐frequency variability in CRU, ERA‐40, and NCEP/NCAR analyses of surface air temperature. Journal of Geophysical Research: Atmospheres. https://doi.org/10.1029/2004jd005306

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.